Proper management of data is required for organizations to perform their missions successfully. For example, modern business infrastructure, such as communication systems, create and log a vast amount of information that may be used to troubleshoot issues that may arise or perform data mining for determining answers for business questions. Additionally, business subsystems rely on storing enormous amounts of data in support of providing goods and services. One major challenge involves the storage of the ever growing volume of data produced. Traditional data compression algorithms would require significant processing power to deal with the need for real-time access of data, and thus, are not practical from a technical and cost perspective. Also, current database management systems largely utilize a relational model, which is not designed with data compression in mind.
Based on the foregoing, there is a need for a database management system and approach that store data as to achieve compression gains.